Rendering is the process of converting a 3D (three dimensional) geometric model into a graphic image. The rendering of an animation scene is a highly time-consuming process, because one animation generally consists of tens of thousands of frames. As the demand for visual effect is getting higher and higher, the resolution of each frame is also getting higher and higher, the number of pixels is getting higher and higher, it may take hours to complete the rendering of a picture.
As the modern graphic hardware acceleration technology progresses, the high speed development of GPU (graphics processing unit) has greatly improved the speed and quality of computer graphic processing, advancing the rapid development of application fields related to computer graphics. Meanwhile, the high speed and parallelism of a GPU rendering pipeline has provided a good platform for a general purpose GPU computation.
In recent years, as the popularization of GPU on battery-powered mobile devices, many Apps that require real-time rendering technology have emerged on such devices. Computation required by such Apps can quickly consume the battery power, on one hand, it is adverse to the life cycle of the battery, more importantly, it reduces the standby time of the mobile device, causing limitation to the user of the device.
Under this background, rendering under the energy consumption precomputation has become an actual demand. Reducing the energy consumption demand of the rendering-related Apps is one of the challenges facing the future computer graphics field. However, currently, there is not a universal solution, and there is much potential in this field that is not explored yet. In the strategy of reducing the energy consumption demand of the graphic App running on battery-powered device, to reduce the computation load in the graphic rendering pipeline is proved to be an effective solution. However, the scope of application of most existing solutions is limited, they are generally applicable to a certain specific App only.
Besides, most methods in the prior art realize the purpose of optimizing resources and reducing energy consumption based on specific graphic pipeline design and hardware. Due to that they are realized through base hardware, the existing hardware structure of the device needs to be changed at high cost.
Some other methods reduce the energy consumption through adaptive device brightness tuning. However, this cannot ensure the image quality, and doesn't actually solve the problem.